Multiplayer ultimatum games and collective fairness in networked communities

Abstract

[Excerpt] The outcome of human interactions is influenced by fairness (Fehr and Fischbacher (2003)), which often stands in disagreement with typical payoff-maximising – and rationality – assumptions. In this context, while the dynamics of fairness in two-person interactions has been given significant attention, mostly in the context of Ultimatum Games (UG) (G¨uth et al. (1982)), the challenge introduced by groups has not received a corresponding emphasis. In many situations individuals decide, collectively, to give up some of their wealth to punish unfair behaviour of others (Fehr and Schmidt (1999)): collective bargaining of work contracts, the Chinese concept of tuangou (or group buying), policymaking by coalitions, international climate summits or the simple act of scheduling a group dinner are a few examples where interactions take place in groups in which individual assessment of fairness contributes to the overall degree of fairness reflected in the (collective) group decision process. Also, the fact that individuals often participate in multiple groups makes it important to understand to which extent our network ties and the way groups are assembled influence overall fairness. Here we present a summary of our recent works in which we employ computer simulations to analyse the population dynamics arising from Multiplayer Ultimatum Game (MUG), where proposals are made to groups, and interactions take place in complex networks of exchange and cooperation (Santos et al. (2017, 2016, 2015)). [...]